Korean Journal of Applied Statistics最新文献

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The impact of the change in the splitting method of decision trees on the prediction power 决策树分裂方法的改变对预测能力的影响
IF 0.2
Korean Journal of Applied Statistics Pub Date : 2022-08-31 DOI: 10.5351/kjas.2022.35.4.517
Youngjae Chang
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引用次数: 0
A study on time series linkage in the Household Income and Expenditure Survey 家庭收支调查的时间序列关联研究
IF 0.2
Korean Journal of Applied Statistics Pub Date : 2022-08-31 DOI: 10.5351/kjas.2022.35.4.553
Sihyeon Kim, B. Seong, Young-Geun Choi, I. Yeo
{"title":"A study on time series linkage in the Household Income and Expenditure Survey","authors":"Sihyeon Kim, B. Seong, Young-Geun Choi, I. Yeo","doi":"10.5351/kjas.2022.35.4.553","DOIUrl":"https://doi.org/10.5351/kjas.2022.35.4.553","url":null,"abstract":"","PeriodicalId":43523,"journal":{"name":"Korean Journal of Applied Statistics","volume":null,"pages":null},"PeriodicalIF":0.2,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44961949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Time series analysis for Korean COVID-19 confirmed cases: HAR-TP-T model approach 韩国新冠肺炎确诊病例的时间序列分析:HAR-TP-T模型方法
IF 0.2
Korean Journal of Applied Statistics Pub Date : 2021-01-01 DOI: 10.5351/kjas.2021.34.2.239
S. Yu, E. Hwang
{"title":"Time series analysis for Korean COVID-19 confirmed cases: HAR-TP-T model approach","authors":"S. Yu, E. Hwang","doi":"10.5351/kjas.2021.34.2.239","DOIUrl":"https://doi.org/10.5351/kjas.2021.34.2.239","url":null,"abstract":"This paper studies time series analysis with estimation and forecasting for Korean COVID-19 confirmed cases, based on the approach of a heterogeneous autoregressive (HAR) model with two-piece t (TP-T) distributed errors. We consider HAR-TP-T time series models and suggest a step-by-step method to estimate HAR coefficients as well as TP-T distribution parameters. In our proposed step-by-step estimation, the ordinary least squares method is utilized to estimate the HAR coefficients while the maximum likelihood estimation (MLE) method is adopted to estimate the TP-T error parameters. A simulation study on the step-by-step method is conducted and it shows a good performance. For the empirical analysis on the Korean COVID-19 confirmed cases, estimates in the HAR-TP-T models of order p = 2, 3, 4 are computed along with a couple of selected lags, which include the optimal lags chosen by minimizing the mean squares errors of the models. The estimation results by our proposed method and the solely MLE are compared with some criteria rules. Our proposed step-by-step method outperforms the MLE in two aspects: mean squares error of the HAR model and mean squares difference between the TP-T residuals and their densities. Moreover, forecasting for the Korean COVID-19 confirmed cases is discussed with the optimally selected HAR-TP-T model. Mean absolute percentage error of one-step ahead out-of-sample forecasts is evaluated as 0.0953% in the proposed model. We conclude that our proposed HAR-TP-T time series model with optimally selected lags and its step-by-step estimation provide an accurate forecasting performance for the Korean COVID-19 confirmed cases.","PeriodicalId":43523,"journal":{"name":"Korean Journal of Applied Statistics","volume":null,"pages":null},"PeriodicalIF":0.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71084380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Statistical Considerations in the Design of Biosimilar Cancer Clinical Trials. 生物类似药癌症临床试验设计中的统计学考虑。
IF 0.2
Korean Journal of Applied Statistics Pub Date : 2011-06-01 DOI: 10.5351/KJAS.2011.24.3.495
Chul Ahn, Seung-Chun Lee
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引用次数: 5
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